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Evolutionary Large-Scale Dynamic Optimization Using Bilevel Variable Grouping
Variable grouping provides an efficient approach to large-scale optimization, and multipopulation strategies are effective for both …
Hui Bai, Ran Cheng, Danial Yazdani, Kay Chen Tan, Yaochu Jin
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Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning Towards Asynchronous Commercial Games
Despite the emerging progress of integrating evolutionary computation into reinforcement learning, the absence of a high-performance …
Hui Bai, Ruimin Shen, Yue Lin, Botian Xu, Ran Cheng
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Large-scale Multiobjective Optimization via Reformulated Decision Variable Analysis
With the rising number of large-scale multiobjective optimization problems (LSMOPs) from academia and industries, some multiobjective …
Cheng He, Ran Cheng, Lianghao Li, Kay Chen Tan, Yaochu Jin
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Large-scale Multiobjective Optimization via Problem Decomposition and Reformulation
Large-scale multiobjective optimization problems (LSMOPs) are challenging for existing approaches due to the complexity of objective …
Lianghao Li, Cheng He, Ran Cheng, Linqiang Pan
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Efficient Evolutionary Search of Attention Convolutional Networks via Sampled Training and Node Inheritance
The performance of deep neural networks is heavily dependent on its architecture and various neural architecture search strategies have …
Haoyu Zhang, Yaochu Jin, Ran Cheng, Kuangrong Hao
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Paired Offspring Generation for Constrained Large-Scale Multiobjective Optimization
Constrained multiobjective optimization problems (CMOPs) widely exist in real-world applications, and they are challenging for …
Cheng He, Ran Cheng, Ye Tian, Xingyi Zhang, Kay Chen Tan, Yaochu Jin
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RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning
Despite the remarkable successes of convolutional neural networks (CNNs) in computer vision, it is time-consuming and error-prone to …
Hao Tan, Ran Cheng, Shihua Huang, Cheng He, Changxiao Qiu, Fan Yang, Ping Luo
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Adaptive Control of Subpopulations in Evolutionary Dynamic Optimization
Multipopulation methods are highly effective in solving dynamic optimization problems. Three factors affect this significantly: 1) the …
Danial Yazdani, Ran Cheng, Cheng He, Jürgen Branke
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Guiding Evolutionary Multiobjective Optimization With Generic Front Modeling
In evolutionary multiobjective optimization, the Pareto front (PF) is approximated by using a set of representative candidate solutions …
Ye Tian, Xingyi Zhang, Ran Cheng, Cheng He, Yaochu Jin
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Techniques for Accelerating Multi-Objective Evolutionary Algorithms in PlatEMO
It has been widely recognized that evolutionary computation is one of the most effective techniques for solving complex optimization …
Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin
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